GIGABYTE G291-280-00
Geekbench AI Score
1353
Single Precision Score
1371
Half Precision Score
747
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| Upload Date | November 02 2025 10:37 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Xeon Silver 4210 |
| System Information | |
|---|---|
| Operating System | Ubuntu 22.04.5 LTS |
| Model | GIGABYTE G291-280-00 |
| Motherboard | GIGABYTE MG51-G21-00 |
| CPU Information | |
|---|---|
| Name | Intel Xeon Silver 4210 |
| Topology | 1 Processor, 10 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 85 Stepping 7 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 251.09 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
910
169.2 IPS |
|
|
Image Classification (HP)
|
100% |
914
169.9 IPS |
|
|
Image Classification (Q)
|
99% |
514
95.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1154
18.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1306
21.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
511
8.30 IPS |
|
|
Pose Estimation (SP)
|
100% |
1867
2.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
1881
2.20 IPS |
|
|
Pose Estimation (Q)
|
96% |
1864
2.18 IPS |
|
|
Object Detection (SP)
|
100% |
992
78.7 IPS |
|
|
Object Detection (HP)
|
100% |
994
78.9 IPS |
|
|
Object Detection (Q)
|
85% |
574
46.2 IPS |
|
|
Face Detection (SP)
|
100% |
1944
23.1 IPS |
|
|
Face Detection (HP)
|
100% |
1944
23.1 IPS |
|
|
Face Detection (Q)
|
97% |
1046
12.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
1780
13.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1755
13.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
1052
9.86 IPS |
|
|
Style Transfer (SP)
|
100% |
2476
3.18 IPS |
|
|
Style Transfer (HP)
|
100% |
2515
3.23 IPS |
|
|
Style Transfer (Q)
|
98% |
3209
4.14 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1037
38.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1041
38.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
831
30.8 IPS |
|
|
Text Classification (SP)
|
100% |
810
1.08 KIPS |
|
|
Text Classification (HP)
|
100% |
810
1.08 KIPS |
|
|
Text Classification (Q)
|
92% |
289
388.4 IPS |
|
|
Machine Translation (SP)
|
100% |
1471
25.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1453
25.0 IPS |
|
|
Machine Translation (Q)
|
58% |
228
5.34 IPS |
